Cubegeek

Intangibles in Globalization

Hybrid Vigor gives me something to think about. Although they pioneered the field, GE is finally selling its appliance business:

The decision fits the pattern that Kaj Grichnik and Conrad Winkler discussed in S+B (and in their new book Make or Break), that companies see manufacturing as a cash cow and non-core to their business. They ask the question in this article “How important is industrial capacity to a nation’s well-being?” and offer an alternative:

Old, fossilized plant footprints can become nimble networks; confrontational labor relationships can evolve into constellations of joint interest; outmoded supply chains can be transformed into clearly defined, mutually beneficial partnerships; and stolid aging factories can be retrofitted into showcases of lean manufacturing. Only those companies that appreciate manufacturing, invest in technology, and innovate in this field are likely to prosper.

Networks, labor, partnerships, lean manufacturing. These are all intangibles. Yes, the future of manufacturing lies in a company’s ability to manage its intangibles.

I was especially struck by this case because I often use GE as an example when I talk about intangible value in companies. Despite its significant reliance on manufacturing and infrastructure, GE has traditionally been known for its management capability, for Six Sigma, for being smarter that most—all intangible aspects of business. People instantly get it when I explain that the future of an industrial company like GE is dependent on how well it manages its intangibles.

A week or so ago I was musing about the success of Samsung in the appliance business. I didn't know until this month that they made refrigerators, and they're very nice ones too.

I wonder if some of the intangibles of an innovative company like GE is passed on when units are spun off to other countries with arguably cheaper labor bases. For example when IBM sold the ThinkPad, my favorite brand of laptop computer, to Chinese Lenovo, did all of the lessons of Boca Raton accrue? Experts may recall that back in the early 90s when IBM was cranking up fabs in Florida there was a lot trouble they got into over its profitability - was IBM even smart enough to do it right? Their smarts finally paid off in an excellent product, but are those intangibles passed on, or do consumers not even care any longer about excellence in increasingly sophisticated commodity products?

I'm at the point at which I don't care about VCRs and small analog televisions. Innovations that led me to pay 300 bucks for each now in the hands of a downscaled market might not matter any longer. This is particularly interesting with regard to the energy efficiency of refrigerators. As some of you may know, the labeling mandated on all refrigerators sold in the US alerted consumers to the long term cost of their operation in terms of their electrical efficiency. It cost more to use the fat copper wires and energy efficient motors in the manufacturing process resulting in a higher price for the smart American consumer, goosed as we were by environmentalist legislation to be energy efficient. But in the long term the American consumer saved operating costs on this durable good. Will such matters be considered at all in the global market for refrigerators when GE's intangibles no longer apply?

Hmmm.

I've been interested in the application of BI technology to management inititatives like Six Sigma. Coming from Xerox in the 80s, such corporate-wide management philosophies are how I was born into the world of business. I'm definitely looking forward to examining such prospects more closely as I move forward.

Case Stories: Measure by Measure

In putting together an Essbase management book, I'm digging deep into my memory for engagements I had with customers and prospects and recalling specific issues they had towards which we applied our knowhow and technology.

There's a big national insurance company that has some large earthquake proof buildings in Los Angeles. Let's call them City State. I recall a trip I made out to them in my buddy's new Nissan Maxima. We engaged the customer in a use case design session, reviewing their entire FOCUS-based repository. From all of their source systems, they had 36 dimensions and many more which were set for aggregation in FOCUS. They called us to help them understand how Essbase could be employed. The managers at City State were tasked with serving a large number of customers from different areas across the business. Data from all lines of business were represented in the current FOCUS database and more were scheduled to be added. FOCUS could no longer handle adhoc queries. They wanted to be able to query anything at any time using the full set of dimensions which included a great deal of demographic data. In short, they had a data mining problem but did not wish to invest in data mining technology.

My use case analysis revealed that there were different clusters of interest around the data which could be identified by analyst group, and began a process that could be tied to incentives for the analyst groups. His solution considered both data supply and data demand.

On the demand side, the query process was undisciplined. Any user from any group could build ad-hoc queries against the whole of the FOCUS database. Nobody knew exactly what queries were being run or for what purposes. The users had become accustomed to asking for everything. They had no organized way of qualifying their requirements from IT and were not satisfied by the results.

So I held a workshop  and through that process we discovered that the Fire LOB analysts knew from their own professional experience that demographic information was not pertinent to the number and severity of claims related to fire. Consequently, the value of demographic dimensional data for that subset of insurance vehicles was de-emphasized and other dimensional attributes, like roofing type & proximity to hydrants were emphasized. We were able to establish a framework through which City State could confidently gather all of the data attributes on all of their lines of business and provide strict guidelines for marting that data to the various user groups.

Once this process of generating requirements was made demonstrated, the path to solving supply and demand issues for City State was made clear. This made blocking and tackling projects a great deal more responsive to the needs of the analyst communities, and gave IT a way to make sense of the backlog and frustrations. Once analysts 'got it' with regard to looking at a set of measures and then associating the most key dimensions to them both sides could see what work was required that could get them through development smartly.

You can follow this kind of guide for your purposes. What are the problem areas that analysts recognize? You can ask this realizing that nobody may have been assigned to solve the problem - that management is busy elsewhere, but the folks in the cubes know that the problem is real. It might start with a very simple metric. How long are people on hold for customer service? Or how about Number of exempt employees with a Masters or Doctorate degrees expressed as a percentage of the total number of exempt employees? It doesn't take too much creativity to realize that any number of business issue can be quantified in this manner.

The next step obviously is to consider within the vast resources of your company's computer generated data, which systems might have information that could credibly generate a dataset worthy of analysis. Certainly any number of operational systems might contain that information. And that would be easy if analysts are struggling to get reports out of the current systems which might provide some insight. HR analysts might know that total number of exempt employees are in one system, but that number of masters or doctorate degrees by employee is in another system. The merging of these two would be the job of the new project manager who requires the assistance of those current data stewards. The analysts can contribute by drawing a reasonable box around the universe of data to be explored, and senior managers can consider what priorities are to be emphasized based upon expectations of what will be found in the data. This insures that the area of inquiry is credible and actionable.

HP + EDS = Enterprise Clouds?

A couple years ago I was ready to quit private contracting and subcontracting. I wanted to join a big deal company that really understood financial data warehousing. I had two choices, and ironically they were looking at me too. They were Beacon Analytics / Answerthink and Knightsbridge. I had worked with Knightsbridge in a sales capacity and I found them to be a very tight organization. They had people who worked with Embarcadero Technologies and they were seriously well managed - enough to walk away from crazy hungry claims of the sort that sink many services companies. I decided on Answerthink and soon after I recall that Knightsbridge was sold to HP.

The news that Knightsbridge went to HP was somewhat strange. What HP did have was a very aggressive attitude towards hosting all the hot enterprise technologies, including and especially the Hyperion suite. What they didn't have was a track record as being a company that could be counted on to deliver all that. Perhaps their purchase indicated that they were ready to change all that.

It had been my experience that most customers who had committed to HP hardware, especially those on HPUX were woefully behind in OLAP and price-performance.  Expertise with Essbase and HPUX was rare indeed. After a time, IBM was the leader in Unix hosting of Hyperion apps and Essbase, whereas once upon a time, Essbase on Sun was the killer app. HP was about tied with Redhat from what I could see in the field, which meant essentially that it was an academic release.

Part of the reason was that Hyperion had pursued, for a short time, a relationship with the engineering support organization of Sun. They must have done something similar when it came to IBM after I departed. What that comprised was a deal whereby Hyperion developers could get up to date hardware, compilers and advice on how to develop for the OS kernels, memory models and various subsystems particular to the OS/hardware combinations. Who knows if such things go on today.

By the time I had been at Answerthink for an appreciable period, I came across HP again. This time going great guns about 64 bit computing. It was something and still continues to be something to get very excited about. What I've personally been able to accomplish on the HP Superdome practically defies description in the ordinary world of Hyperion apps. For a short time, we had some very interesting momentum. Such momentum is very difficult to sustain without a real paying customer, but a company like HP can afford to keep BizDev folks buzzing for a good long time, as well as keep configuration engineers setting up performance laboratories that make the case for blistering performance. The trick is maintaining the mix with a consulting organization who has a big customer attention, meaning bucks.

This is clearly what EDS provides. And I rather like the idea that HP is doing this the technical way rather than IBM's way of the brownbagging of Global Services plus the high concept dinner of PWC. The only equivalent thing left would be a Sun Micro acquisition of CSC. Then what's left? Perhaps Google acquires Tata? SAP acquires Infosys? That would be a shocker. But it gives me a clue about what could also be going on here. Like it or not corporate IT has failed. What have they failed to do? They have failed to keep Salesforce and Tata out of their business. They have failed to deal with grid computing, and they have failed to get their datacenters and moreover their global applications functioning as well as the web providers of the world have. There is a huge gap between what the largest companies like Boeing can muster in their IT and what modestly successful websites like The Washington Post online can do. The very idea of serving up enterprise data to more than 10,000 simultaneous users gives most IT organizations a severe case of cramps. If you can't do that in the online world, you're lower than toast.

So how do you ramp up internal corporate IT and enterprise data to the sub-second million-user scale of external websites? It may be apples and oranges unless and until you consider what I've seen in HP's labs, which is several hundered Essbase cubes running simultaneously. What kind of collaboration is necessary to get the corporate accounting data running in a 64bit cloud? That's the kind of thing we should begin to see if and when HP consumes EDS (or Google + Salesforce + Infosys happens). See?

It's time to take the lessons of Web 2.0 and even 1.5 and apply them to corporate IT 1.0. It's time for internal enterprise applications to run faster and be more integrated using some of the same technology that makes Google a faster way to get your company's 10Q data than searching through shared drives in your Microsoft Domain. Sound like SAP? Sound like Oracle? Yep. Only large cross functional services organizations teamed up with serious compute clouds and grids can do that. If that's what HP has in mind with EDS, it's going to be a brave new world.

IBM + Google = Grid Apps Nirvana

Ignore this story at your own peril:

IBM and Google plan to exploit their common technological world view and considerable talent to build a worldwide network, or cloud, of servers from which consumers and businesses will tap everything from online soccer schedules to advanced engineering applications.

"It's the story of our lifetime," said Schmidt.

And

IBM and Google on Monday released details on their "academic cluster computing initiative" to provide data centers for remote computer programming.

The centers would allow a larger number of students and programmers to have access and processing power for writing software code involving massive amounts of data over the Internet, a practice known as "cloud computing."

The program, which is already under way at the University of Washington, will also be rolled out at Carnegie-Mellon University, the Massachusetts Institute of Technology, Stanford University, the University of California at Berkeley and the University of Maryland. IBM and Google will provide hardware, software and services.

"The goal of this initiative is to improve computer science students' knowledge of highly parallel computing practices to better address the emerging paradigm of large-scale distributed computing," said IBM in a statement.